Artificial Neural Network detail syllabus for Instrumentation & Control Engineering (ICE), 2019-20 scheme is taken from AKTU official website and presented for AKTU students. The course code (REC054), and for exam duration, Teaching Hr/Week, Practical Hr/Week, Total Marks, internal marks, theory marks, and credits do visit complete sem subjects post given below.
For all other ice 5th sem syllabus for b.tech 2019-20 scheme aktu you can visit ICE 5th Sem syllabus for B.Tech 2019-20 Scheme AKTU Subjects. For all other Departmental Elective-I subjects do refer to Departmental Elective-I. The detail syllabus for artificial neural network is as follows.
Unit I
For the complete syllabus, results, class timetable and more kindly download iStudy. It’s a lightweight, easy to use, no images, no pdfs platform to make student’s life easier.
Unit II
Back propagation networks : (BPN) Architecture of feed forward network, single layer ANN, multilayer perceptron, back propagation learning, input – hidden and output layer computation, back propagation algorithm, applications, selection of tuning parameters in BPN, Numbers of hidden nodes, learning. 8
Unit III
Activation & Synaptic Dynamics : Introduction, Activation Dynamics models, synaptic Dynamics models, stability and convergence, recall in neural networks. Basic functional units of ANN for pattern recognition tasks: Basic feed forward, Basic feedback and basic competitive learning neural network. Pattern association, pattern classification and pattern mapping tasks. 8
Unit IV
For the complete syllabus, results, class timetable and more kindly download iStudy. It’s a lightweight, easy to use, no images, no pdfs platform to make student’s life easier.
Unit V
Competitive learning neural networks : Components of CL network pattern clustering and feature. Mapping network, ART networks, Features of ART models, character recognition using ART network. Applications of ANN: Pattern classification – Recognition of Olympic games symbols, Recognition of printed Characters. Neocognitron -Recognition of handwritten characters. NET Talk: to convert English text to speech. Recognition of consonant vowel (CV) segments, texture classification and segmentation. 8
Reference Books:
- S. Raj Sekaran , Vijayalakshmi Pari,” Neural networks, Fuzzy logic and Genetic Algorithms”, PHI Publication.
- Elaine Rich and Kevin Knight, “Artificial Intelligence”, TMH Publication.
- Rajiv Chopra, Machine Learning, Khanna Publishing House.
- B. Yegnanarayana, “Artificial neural Networks”, PHI Publication.
For detail syllabus of all other subjects of B.Tech Ice, 2019-20 regulation do visit Ice 5th Sem syllabus for 2019-20 Regulation.
Don’t forget to download iStudy for the latest syllabus, results, class timetable and more.